Automated video analytic systems may use background subtraction (BGS) and processes to distinguish visible foreground objects of interest relative to other visual elements determined to be background data within the video data, and to thereby enable detection and observation of said foreground objects in processed video data inputs. Such information processing systems may receive images or image frame data captured by video cameras or other image capturing devices, wherein individual frames of video data are processed or analyzed by an object detection system in the information processing system to identify and track the presence and movement of objects detected within the video data over time.
However, automated background subtraction systems may perform poorly due to complexities in interpreting image data attributes. Accurately distinguishing and tracking multiple objects present within image data, such as a vehicles or pedestrians in a street scene, may be challenging due to large variability in amounts of reflected light over time generated by changing weather conditions, for example due to progressive transitions between sunny, cloudy, nighttime lighting, and fast and intermittent changes via transient moving cloud shadows, etc. Temporary occlusions caused by other moving objects may also pose problems in tracking individual objects. A wide variety of reflected or occluded lighting profiles must be processed that may be caused by different moving objects and transient cloud shadows, wherein each may move at different speeds of movement relative to the video cameras. Even a minor change in lighting with respect to strong visual textures may cause incorrect foreground classification in video analytic systems. Thus, high rates of false positive detections, or low rates of accuracy in detecting true events, may generally limit the usefulness and trustworthiness of such systems in finding and tracking objects of interest in video data in real-time, or to otherwise meet constraints imposed in performing under real world conditions.